Default Notebook Extensions for Better Presentations:
Imgur

Present working directory path

pwd
'C:\\Users\\Administrator\\Documents\\GitHub\\DSAIML\\00-Python\\00-notebooks'
from sklearn import datasets
import pandas as pd
wine_data = pd.DataFrame(datasets.load_wine().data)
wine_data.columns = datasets.load_wine().feature_names
wine_data.head(5)
alcohol malic_acid ash alcalinity_of_ash magnesium total_phenols flavanoids nonflavanoid_phenols proanthocyanins color_intensity hue od280/od315_of_diluted_wines proline
0 14.23 1.71 2.43 15.6 127.0 2.80 3.06 0.28 2.29 5.64 1.04 3.92 1065.0
1 13.20 1.78 2.14 11.2 100.0 2.65 2.76 0.26 1.28 4.38 1.05 3.40 1050.0
2 13.16 2.36 2.67 18.6 101.0 2.80 3.24 0.30 2.81 5.68 1.03 3.17 1185.0
3 14.37 1.95 2.50 16.8 113.0 3.85 3.49 0.24 2.18 7.80 0.86 3.45 1480.0
4 13.24 2.59 2.87 21.0 118.0 2.80 2.69 0.39 1.82 4.32 1.04 2.93 735.0

Markdown syntax

markdown syntax: https://www.markdownguide.org/basic-syntax/

Accessing/loading a files

If File is available in the same current working directory folder

import pandas as pd

df1 = pd.read_csv(
    'hcpuniverse.csv', sep=";"
)  #goback to the previous parent directory files other than present working directory


df1.shape
(3681, 6)



(3681, 6)

If the File is available in the folder curresponding the same working directory location

import pandas as pd

df2 = pd.read_csv(
    '01A-data/hcpuniverse.csv', sep=";"
)  #goback to the previous parent directory files other than present working directory
df2.shape
(3681, 6)



(3681, 6)

OR

import pandas as pd

df3 = pd.read_csv(
    './01A-data/hcpuniverse.csv', sep=";"
)  #goback to the previous parent directory files other than present working directory
df3.shape
(3681, 6)



(3681, 6)

Accessing/loading a file which present in other than current/present working directory exact parent of current

import pandas as pd

df4 = pd.read_csv(
    '../01-data/hcpuniverse.csv', sep=";"
)  #goback to the previous parent directory files other than present working directory
df4.shape
(3681, 6)



(3681, 6)
df4.head()
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE

Accessing/loading a file which present in other than current/present working directory grand parent of current path

import pandas as pd
df5 = pd.read_csv('../../00-Python/hcpuniverse.csv',sep=";") #goback to the previous/parent directory files
df5.head()
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE
import pandas as pd
df6 = pd.read_csv('../../../DSAIML/hcpuniverse.csv',sep=";") #goback to the previous/parent directory files
df6.head()
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE

Accessing/loading a file which present in other than current/present working directory other than grand parent of current path, super path let’s say computer account name path

import pandas as pd

df7 = pd.read_csv(
    '~/hcpuniverse.csv', sep=";"
)  #goback to the computer's account named directory(if the file located there) "C:\Users\Administrator" is nothing but ~
df7.head()
c_First_Name h_First_Name c_Last_Name h_Last_Name c_Title h_Title
0 Brian BRIAN Kelly KELLY Medicine PHYSICAL MEDICINE AND REHABILITATION
1 Rahul RAHUL Sharma SHARMA Laboratory Director PHYSICAL MEDICINE AND REHABILITATION
2 Kashif KASHIF Khan KHAN Anesthesia GERIATRIC MEDICINE
3 Mark MARK Smith SMITH Anesthesia INTERNAL MEDICINE
4 Paul PAUL Harris HARRIS Apprenticeship in Joinery FAMILY PRACTICE

Tables Generation

Tables Generator: https://www.tablesgenerator.com/markdown_tables

IPython.display Module:

How to Display Contents of Different Types in Jupyter Notebook/Lab:
https://coderzcolumn.com/tutorials/python/how-to-display-contents-of-different-types-in-jupyter-notebook-lab

LaTeX/Mathematics codes for statistical symbols

LaTeX/Mathematics:
https://en.wikibooks.org/wiki/LaTeX/Mathematics
https://towardsdatascience.com/write-markdown-latex-in-the-jupyter-notebook-10985edb91fd
https://personal.math.ubc.ca/~pwalls/math-python/jupyter/latex/
https://www.overleaf.com/learn
(\cos (2\theta) = \cos^2 \theta - \sin^2 \theta)

[\cos (2\theta) = \cos^2 \theta - \sin^2 \theta]

$\cos (2\theta) = \cos^2 \theta - \sin^2 \theta$

cos(2θ)=cos2θsin2θ\cos (2\theta) = \cos^2 \theta - \sin^2 \theta $\sum$

$\mathtt{afaf}$

$\mathscr{ABCD}$

$\widehat{AAA}$

$\nsupseteq$

$\Phi, \phi and \varphi$

A matrix in text must be set smaller: $\bigl(\begin{smallmatrix} a&b \ c&d \end{smallmatrix} \bigr)$ to not increase leading in a portion of text.

[ \begin{matrix} a & b & c
d & e & f
g & h & i \end{matrix} ]

$\Phi$

$e^{i \pi} + 1 = 0$

$\forall x$

arg1arg2x2eiπAiBijargn\frac{arg 1}{arg 2} \\ x^2\\ e^{i\pi}\\ A_i\\ B_{ij}\\ \sqrt[n]{arg}

Given : $\pi = 3.14$ , $\alpha = \frac{3\pi}{4}\, rad$ ω=2πff=cλλ0=θ2+δΔλ=1λ2\omega = 2\pi f \\ f = \frac{c}{\lambda}\\ \lambda_0=\theta^2+\delta\\ \Delta\lambda = \frac{1}{\lambda^2}

$ \delta $ $ \Delta $

$k_{n+1} = n^2 + k_n^2 - k_{n-1}$

$\frac{n!}{k!(n-k)!} = \binom{n}{k}$

$\begin{equation} \frac{ \begin{array}[b]{r} \left( x_1 x_2 \right)
\times \left( x’_1 x’_2 \right) \end{array} }{ \left( y_1y_2y_3y_4 \right) } \end{equation}$

$ \int\limits_a^b $

$ 50 \textrm{ apples} \times 100 \textbf{ apples} = \textit{lots of apples}^2 $

$ \begin{equation} x = a_0 + \cfrac{1}{a_1 + \cfrac{1}{a_2 + \cfrac{1}{a_3 + \cfrac{1}{a_4} } } } \end{equation} $

$ \binom{n}{k} = \frac{n!}{k!(n-k)!} $

J=dfdx=[fx1fxn]=[f1x1f1xnfmx1fmxn]\mathbf{J} = \frac{d \mathbf{f}}{d \mathbf{x}} = \left[ \frac{\partial \mathbf{f}}{\partial x_1} \cdots \frac{\partial \mathbf{f}}{\partial x_n} \right] = \begin{bmatrix} \frac{\partial f_1}{\partial x_1} & \cdots & \frac{\partial f_1}{\partial x_n} \\ \vdots & \ddots & \vdots \\ \frac{\partial f_m}{\partial x_1} & \cdots & \frac{\partial f_m}{\partial x_n} \end{bmatrix}

Embedding Images From Online and Local Folder

Imgur

Embedding Images From Local Folder:
Some
Above Code we can Use This Below Code as per Obsidian Point of view to display in the Obsidian platform:
![[imgsAudVid/Engelbart.jpg]]

Using Python Code

from IPython.display import Image
i = Image(filename='../03-imgs/1_N1tiuQF9phkp8eYlum9twA.jpeg')
i # list of things you can pass to a dataframe

jpeg

Download Notebook as PDF, markdown, html and others:

Note: To get above please go through below document to install sufficient software tools:`

nbconvert: Convert Notebooks to other formats:https://nbconvert.readthedocs.io/en/latest/index.html

First Approach

Source: https://mpievolbio-scicomp.pages.gwdg.de/blog/post/2020-12-09_pandoc_vs_nbconvert/
pandoc --to pdf --from ipynb -o Notebook.pdf Notebook.ipynb
OR
Download as PDF via LaTex(.pdf)
OR
Goto Chrome three dots choose print option and Save as PDF

Second Approach

Use Another Approach like below:
https://jupytext.readthedocs.io/en/latest/using-cli.html

Third Approach

Using nbconvert with all necessary installation mentioned below:
https://nbconvert.readthedocs.io/en/latest/install.html

Also check other needed packages to work and export as different file types(md,pdf,html…etc):

Sharing and Publishing Jupyter Notebooks and Exporting the Jupyter Notebook:
https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/install.html https://reproducible-science-curriculum.github.io/publication-RR-Jupyter/02-exporting_the_notebook/index.html https://www.codegrepper.com/code-examples/shell/install+nbextensions
A collection of various notebook extensions for Jupyter:
https://github.com/ipython-contrib/jupyter_contrib_nbextensions

# Sample Code
import matplotlib.pyplot as plt
import numpy as np

xpoints = np.array([1, 8])
ypoints = np.array([3, 10])

plt.plot(xpoints, ypoints)
plt.show()

png

png

Embedding Audio Files to the MD File As Per Obsidian Point of View

(Neither displays in ipynb or md file directly from jupyter but it displays in the Obsidian platfrom)
![[imgsAudVid/Excerpt from Mother of All Demos (1968).ogg]]

Embedding Video Files to the MD File As Per Obsidian Point of View

(Neither displays in ipynb or md file directly from jupyter but it displays in the Obsidian platfrom)

import IPython
IPython.display.Audio('imgsAudVid/Excerpt from Mother of All Demos (1968).ogg')
from IPython.display import Video
Video("imgsAudVid/SampleVIDEO1.mp4", embed=True)
from IPython.display import YouTubeVideo
YouTubeVideo('Gx1I_J_Y_Is', width=400, height=200)

Embedding Tweets

(Neither displays in ipynb or md file directly from jupyter but it displays in the Obsidian platfrom)

print("hello world")
hello world
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
new_array = np.logspace(1., 10., num=120, endpoint=True, base=2)
new_array
array([   2.        ,    2.10764261,    2.22107869,    2.34062004,
          2.46659527,    2.59935064,    2.73925109,    2.88668115,
          3.0420461 ,    3.20577299,    3.37831188,    3.56013703,
          3.75174825,    3.95367224,    4.16646404,    4.39070858,
          4.62702224,    4.87605462,    5.13849024,    5.41505049,
          5.70649558,    6.01362662,    6.33728785,    6.67836895,
          7.03780748,    7.41659147,    7.8157621 ,    8.23641662,
          8.67971131,    9.1468647 ,    9.6391609 ,   10.15795312,
         10.70466741,   11.28080658,   11.88795431,   12.52777953,
         13.20204097,   13.91259205,   14.66138591,   15.45048084,
         16.28204588,   17.15836684,   18.08185253,   19.05504144,
         20.08060864,   21.1613732 ,   22.30030592,   23.50053749,
         24.76536709,   26.09827147,   27.5029145 ,   28.98315726,
         30.54306861,   32.18693642,   33.91927935,   35.74485923,
         37.66869421,   39.69607249,   41.83256692,   44.08405027,
         46.45671139,   48.95707223,   51.59200575,   54.36875483,
         57.29495217,   60.37864128,   63.62829855,   67.05285662,
         70.66172888,   74.46483535,   78.47262997,   82.69612933,
         87.14694294,   91.83730514,   96.78010877,  101.98894053,
        107.47811842,  113.26273102,  119.35867902,  125.78271891,
        132.552509  ,  139.68665803,  147.20477627,  155.12752945,
        163.47669555,  172.27522466,  181.54730209,  191.31841483,
        201.61542161,  212.46662673,  223.90185787,  235.95254808,
        248.65182216,  262.03458775,  276.13763125,  290.99971896,
        306.66170362,  323.16663674,  340.5598869 ,  358.88926448,
        378.20515309,  398.56064803,  420.01170228,  442.61728026,
        466.43951995,  491.54390367,  517.99943809,  545.8788439 ,
        575.25875571,  606.21993272,  638.84748069,  673.23108587,
        709.46526156,  747.64960787,  787.88908554,  830.29430441,
        874.9818275 ,  922.07449141,  971.70174396, 1024.        ])
# Silly example data
bp_x = np.linspace(0, 2*np.pi, num=40, endpoint=True)
bp_y = np.sin(bp_x)

# Make the plot
plt.plot(bp_x, bp_y, linewidth=3, linestyle="--",
         color="blue", label=r"Legend label $\sin(x)$")
plt.xlabel(r"Description of $x$ coordinate (units)")
plt.ylabel(r"Description of $y$ coordinate (units)")
plt.title(r"Title here (remove for papers)")
plt.xlim(0, 2*np.pi)
plt.ylim(-1.1, 1.1)
plt.legend(loc="lower left")
plt.show()

png


import sys; 
print(sys.executable)
C:\Users\Administrator\anaconda3\python.exe

Embedding Slideshare, pinterest, instagram, tumblr, infographics, Handbooks, Mindmaps

Slideshare

Sql Server Basics from rainynovember12

Pinterest

Instagram

View this post on Instagram

A post shared by Data Structure | Algorithm (@python4coding)

tumblr

https://theinsaneapp.tumblr.com/post/687319755653251072/machine-learning-algorithms-read-in-detail

infographics


Handbooks


Mindmaps